SEEKING NEW PhD STUDENTS
FOR FALL 2014: Several topics
in optimization. I am looking for original thinkers who have a good knowledge
of optimization algorithms and skills in software development (especially experience
with parallel or concurrent algorithms). Preference for domestic applicants,
though foreign applicants with strong records may apply.
Optimization algorithms and
software. Faster and more effective algorithms and software for
nonlinear, mixed-integer, and linear programming.
Feasibility and infeasibility in
optimization. Ways of reaching a feasible solution more quickly
for nonlinear and mixed-integer programs, and of analyzing infeasible
optimization models. Spin-off applications from algorithms for
assistants. Automated tools for analyzing and debugging
optimization models. For example, one tool analyzes the shape of nonlinear
functions and regions to help select the correct solver.
Applied optimization. Examples
include transistor sizing, DSP task-to-processor assignment, flexible
manufacturing systems, forestry, scheduling, task assignment in cloud
computing, channel assignment in wireless networks, 3G communications
Data classifiers. A new
approach for finding good data classifiers arises from an infeasibility
analysis algorithm. What is the best way to use this to develop
better data classifiers?